This article talks about how genomic evaluation has changed how sires are selected in the major dairy and beef breeds. The population of bulls being evaluated for dairy herd sire usage has grown perhaps 10 to 20 fold through the use of genomic screening of potential sires prior to purchase and admission to a bull stud. The number actually standing at stud has not changed. Genomic evaluation in both beef and dairy breeds has been an important component in the substantial growth of the beef (sire) on dairy (cow) phenomena.

Implementing an appropriate breeding program is crucial to control fluctuation in performance, enhance adaptation, and further improve the crossbred population of dairy cattle. Five alternative breeding programs (BPs) were modeled considering available breeding units in the study area, the existing crossbreeding practices, and the future prospects of dairy research and development in Ethiopia. The study targeted 143,576 crossbred cows of 54,822 smallholder households in the Arsi, West Shewa, and North Shewa zones of the Oromia Region, as well as the North Shewa zone of the Amhara Region. The alternative BPs include conventional on-station progeny testing (SPT), conventional on-farm progeny testing (FPT), conventional on-station and on-farm progeny testing (SFPT), genomic selection (GS), and genomic progeny testing (GPT). Input parameters for modeling the BPs were taken from the analysis of long-term data obtained from the Holetta Agricultural Research Center and a survey conducted in the study area. ZPLAN+ software was used to predict estimates of genetic gain (GG) and discounted profit for goal traits. The predicted genetic gains (GGs) for milk yield (MY) per year were 34.52 kg, 49.63 kg, 29.35 kg, 76.16 kg, and 77.51 kg for SPT, FPT, SFPT, GS, and GPT, respectively. The GGs of the other goal traits range from 0.69 to 1.19 days per year for age at first calving, from 1.20 to 2.35 days per year for calving interval, and from 0.06 to 0.12 days per year for herd life. Compared to conventional BPs, genomic systems (GPT and GS) enhanced the GG of MY by 53%-164%, reduced generation interval by up to 21%, and improved the accuracy of test bull selection from 0.33 to 0.43. The discounted profit of the BPs varied from 249.58 Ethiopian Birr (ETB, 1 USD = 39.55696 ETB) per year in SPT to 689.79 ETB per year in GS. Genomic selection outperforms SPT, SFPT, and FPT by 266, 227%, and 138% of discounted profit, respectively. Community-based crossbreeding accompanied by GS and gradual support with progeny testing (GPT) is recommended as the main way forward to attain better genetic progress in dairy farms in Ethiopia and similar scenarios in other tropical countries.

The Angoni cattle breed\'s contribution to the country\'s economy is crucial, as it significantly contributes to animal draught power and meat supply, despite not being primarily used for milk production. Despite its importance, there is a lack of comprehensive research conducted to characterize this breed. This study aimed to investigate the impact of the generation interval (GI) and season of birth (SB) on key reproductive parameters, including age at first calving (AFC), birth weight (BW), and calving interval (CI) in angoni cattle. Data sourced from the Angónia Research Station (ARS) included records for 425 heifers\' AFC, 1684 calves\' BW, and 1272 cows\' CI. The study calculated overall averages and explored the relationships between generation intervals, the season of birth, and the aforementioned reproductive traits. The mean values for AFC, BW, and CI were determined as 1475.40 days, 18.49 kg, and 634.62 days, respectively. The analysis revealed that both generation interval and season of birth exhibited weak relationships, and their influence did not yield significant effects on the reproductive traits under investigation (P > 0.05). The observed variability ranged from 0.37 to 0.46% for AFC, 0.10-0.01% for BW, and 0.11-0.26% for CI. In conclusion, this study determined that neither generation interval nor birth season significantly affected the age at first calving, birth weight, or calving interval in Angoni cattle.

With a history tracing back to at least the 18th century and a substantial global influence on various breeds, Polish Arabian horse population is of paramount importance for both breeders and conservationists. However, its genetic makeup and the population dynamics are still not well understood. This study presents an analysis of the modern Polish Arabian horse population using pedigree data, focusing on the breed\'s genetic diversity and population structure. Our analysis encompassed 1 498 individuals defined as the reference population (RP) and their 11 065 ancestors, which resulted in the dataset of 12 254 individuals (total population). We traced their genealogy to assess inbreeding coefficients (F), founder effects, and genetic variability measures such as the effective number of founders (fe), ancestors (fa), or founder genome equivalents (fge). The results indicated a good pedigree quality with an average of 28.1 maximum traced generations, revealing high pedigree completeness for initial generations with a decline beyond the seventh generation. The genetic diversity parameters showed a considerable bottleneck effect, with an effective number of founders at 73, which reflects a substantial loss of genetic diversity over time. Despite the vast total number of founders (852), only a few have had a lasting impact on the current population, signaling the need for revised breeding strategies to maintain diversity. The study identified a slight but consistent rise in inbreeding over the last century, with a marginal recent decline, and a significant difference in the contribution of various founders. The average F was 5.8%, with 99.6% of the reference population being inbred. The analysis of effective population size (Ne) highlighted potential risks for genetic diversity, urging for revision of breeding goals to consider a wider array of founder lineages. The study indicated that stallions belonging to RP can be attributed to 15 distinct sirelines, whereas mares to 45 unique damlines, more than considered in the current breeding program (8 and 15, respectively). Conclusively, the study underlines the need for ongoing monitoring and strategic breeding to maintain and enhance the genetic diversity of Polish Arabians, considering the breed\'s historical significance and contemporary genetic challenges.

Estimating key epidemiological parameters, such as incubation period, serial interval (SI), generation interval (GI) and latent period, is essential to quantify the transmissibility and effects of various interventions of COVID-19. These key parameters play a critical role in quantifying the basic reproduction number. With the hard work of epidemiological investigators in South Korea, estimating these key parameters has become possible based on infector-infectee surveillance data of COVID-19 between February 2020 and April 2021. Herein, the mean incubation period was estimated to be 4.9 days (95% CI: 4.2, 5.7) and the mean generation interval was estimated to be 4.3 days (95% CI: 4.2, 4.4). The mean serial interval was estimated to be 4.3, with a standard deviation of 4.2. It is also revealed that the proportion of presymptomatic transmission was ~57%, which indicates the potential risk of transmission before the disease onset. We compared the time-varying reproduction number based on GI and SI and found that the time-varying reproduction number based on GI may result in a larger estimation of Rt, which refers to the COVID-19 transmission potential around the rapid increase of cases. This highlights the importance of considering presymptomatic transmission and generation intervals when estimating the time-varying reproduction number.

BACKGROUND: The serial interval is the period of time between symptom onset in the primary case and symptom onset in the secondary case. Understanding the serial interval is important for determining transmission dynamics of infectious diseases like COVID-19, including the reproduction number and secondary attack rates, which could influence control measures. Early meta-analyses of COVID-19 reported serial intervals of 5.2 days (95% CI: 4.9-5.5) for the original wild-type variant and 5.2 days (95% CI: 4.87-5.47) for Alpha variant. The serial interval has been shown to decrease over the course of an epidemic for other respiratory diseases, which may be due to accumulating viral mutations and implementation of more effective nonpharmaceutical interventions. We therefore aggregated the literature to estimate serial intervals for Delta and Omicron variants.
METHODS: This study followed Preferred Reporting Items for Systematic Reviews and Meta-analyses guidelines. A systematic literature search was conducted of PubMed, Scopus, Cochrane Library, ScienceDirect, and preprint server medRxiv for articles published from April 4, 2021, through May 23, 2023. Search terms were: (\"serial interval\" or \"generation time\"), (\"Omicron\" or \"Delta\"), and (\"SARS-CoV-2\" or \"COVID-19\"). Meta-analyses were done for Delta and Omicron variants using a restricted maximum-likelihood estimator model with a random effect for each study. Pooled average estimates and 95% confidence intervals (95% CI) are reported.
RESULTS: There were 46,648 primary/secondary case pairs included for the meta-analysis of Delta and 18,324 for Omicron. Mean serial interval for included studies ranged from 2.3-5.8 days for Delta and 2.1-4.8 days for Omicron. The pooled mean serial interval for Delta was 3.9 days (95% CI: 3.4-4.3) (20 studies) and Omicron was 3.2 days (95% CI: 2.9-3.5) (20 studies). Mean estimated serial interval for BA.1 was 3.3 days (95% CI: 2.8-3.7) (11 studies), BA.2 was 2.9 days (95% CI: 2.7-3.1) (six studies), and BA.5 was 2.3 days (95% CI: 1.6-3.1) (three studies).
CONCLUSIONS: Serial interval estimates for Delta and Omicron were shorter than ancestral SARS-CoV-2 variants. More recent Omicron subvariants had even shorter serial intervals suggesting serial intervals may be shortening over time. This suggests more rapid transmission from one generation of cases to the next, consistent with the observed faster growth dynamic of these variants compared to their ancestors. Additional changes to the serial interval may occur as SARS-CoV-2 continues to circulate and evolve. Changes to population immunity (due to infection and/or vaccination) may further modify it.

Estimating the differences in the incubation-period, serial-interval, and generation-interval distributions of SARS-CoV-2 variants is critical to understanding their transmission. However, the impact of epidemic dynamics is often neglected in estimating the timing of infection-for example, when an epidemic is growing exponentially, a cohort of infected individuals who developed symptoms at the same time are more likely to have been infected recently. Here, we reanalyze incubation-period and serial-interval data describing transmissions of the Delta and Omicron variants from the Netherlands at the end of December 2021. Previous analysis of the same dataset reported shorter mean observed incubation period (3.2 d vs. 4.4 d) and serial interval (3.5 d vs. 4.1 d) for the Omicron variant, but the number of infections caused by the Delta variant decreased during this period as the number of Omicron infections increased. When we account for growth-rate differences of two variants during the study period, we estimate similar mean incubation periods (3.8 to 4.5 d) for both variants but a shorter mean generation interval for the Omicron variant (3.0 d; 95% CI: 2.7 to 3.2 d) than for the Delta variant (3.8 d; 95% CI: 3.7 to 4.0 d). The differences in estimated generation intervals may be driven by the \"network effect\"-higher effective transmissibility of the Omicron variant can cause faster susceptible depletion among contact networks, which in turn prevents late transmission (therefore shortening realized generation intervals). Using up-to-date generation-interval distributions is critical to accurately estimating the reproduction advantage of the Omicron variant.

Beef cattle breeding programs offer genetic evaluations and consulting services on animal breeding practices to help breeders improve the genetic merit of their herds. Some breeders are more willing to apply best practices and technologies than others. Consequently, the average genetic merit and genetic trends differ across herds. We benchmarked some parameters of an average herd (AVE) and the corresponding parameters of herds with higher genetic merit (TOP), both participating in a commercial Nellore breeding program. Expected progeny differences (EPD) for growth, reproductive and carcass traits and a selection index (SI) of animals born from 2005 to 2019 on 128 farms located in Brazil, Bolivia and Paraguay were used to compute the AVE parameters. The 20 herds with higher mean SI of animals born in the last five birth seasons were classified as TOP herds. The mean SI and EPD of animals born in the last five seasons in the TOP herds were, respectively, 89% and 79% to 206% higher (p ≤ 0.001) than those of animals from the AVE herd. Genetic trends over the entire period were also higher (50% for SI and 31% to 88% separately for each trait, p ≤ 0.006) in the TOP herds compared to the AVE herd. Although the difference in the numbers of cows, bulls and calves between the TOP and AVE herds did not reach statistical significance (p = 0.175, p = 0.273 and p = 0.061, respectively), the numbers of progeny per cow and per bull were 21% (p = 0.012) and 26% (p = 0.047) higher in the TOP herds, respectively. Multiple ovulation and embryo transfer and in vitro fertilization and embryo transfer (MOET/IVF) accounted for a higher percentage of births in the TOP herds compared to AVE (24.6% vs. 12.5%, p = 0.002). The generation interval was 17% shorter (p < 0.001) in the TOP herds compared to AVE. The average inbreeding coefficient of animals from the TOP herds (1.08 ± 0.52%) did not differ (p = 0.78) from that of AVE animals (1.26 ± 0.96%). In general, AVE herds are evolving in the desirable direction but differences in genetic merit between AVE and TOP herds are increasing over time. The more frequent use of MOET/IVF, a lower cow-to-bull ratio, and a larger family size (progeny per cow or per bull) can help achieve larger selection differentials and increase genetic trends and average genetic merits of TOP herds compared to AVE herds.

Genomic selection increases accuracy and decreases generation interval, accelerating genetic changes in populations. Assumptions of genetic improvement must be addressed to quantify the magnitude and direction of change. Genetic trends of US dairy cattle breeds were examined to determine the genetic gain since the implementation of genomic evaluations in 2009. Inbreeding levels and generation intervals were also investigated. Breeds included Ayrshire, Brown Swiss, Guernsey, Holstein (HO), and Jersey (JE), which were characterized by the evaluation breed the animal received. Mean genomic predicted breeding values (PBV¯) were analyzed per year to calculate genetic trends for bulls and cows. The data set contained 154,008 bulls and 33,022,242 cows born since 1975. Breakpoints were estimated using linear regression, and nonlinear regression was used to fit the piecewise model for the small sample number in some years. Generation intervals and inbreeding levels were also investigated since 1975. Milk, fat, and protein yields, somatic cell score, productive life, daughter pregnancy rate, and livability PBV¯ were documented. In 2017, 100% of bulls in this data set were genotyped. The percentage of genotyped cows has increased 23 percentage points since 2010. Overall, production traits have increased steadily over time, as expected. The HO and JE breeds have benefited most from genomics, with up to 192% increase in genetic gain since 2009. Due to the low number of observations, trends for Ayrshire, Brown Swiss, and Guernsey are difficult to infer from. Trends in fertility are most substantial; particularly, most breeds are trending downwards and daughter pregnancy rate for JE has been decreasing steadily since 1975 for bulls and cows. Levels of genomic inbreeding are increasing in HO bulls and cows. In 2017, genomic inbreeding levels were 12.7% for bulls and 7.9% for cows. A suggestion to control this is to include the genomic inbreeding coefficient with a negative weight to the selection index of bulls with high future genomic inbreeding levels. For sires of bulls, the current generation intervals are 2.2 yr in HO, 3.2 in JE, 4.4 in Brown Swiss, 5.1 in Ayrshire, and 4.3 in Guernsey. The number of colored breed bulls in the United States is currently at an extremely low level, and this number will only increase with a market incentive or additional breed association involvement. Increased education and extension could be beneficial to increase knowledge about inbreeding levels, use of genomics and genetic improvement, and genetic diversity in the genomic selection era.

Severe acute respiratory coronavirus 2 (SARS-CoV-2) infections have been associated with substantial presymptomatic transmission, which occurs when the generation interval-the time between infection of an individual with a pathogen and transmission of the pathogen to another individual-is shorter than the incubation period-the time between infection and symptom onset. We collected a dataset of 257 SARS-CoV-2 transmission pairs in Japan during 2020 and jointly estimated the mean incubation period of infectors (4.8 days, 95 % CrI: 4.4-5.1 days), mean generation interval to when they infect others (4.3 days, 95 % credible interval [CrI]: 4.0-4.7 days), and the correlation (Kendall\'s tau: 0.5, 95 % CrI: 0.4-0.6) between these two epidemiological parameters. Our finding of a positive correlation and mean generation interval shorter than the mean infector incubation period indicates ample infectiousness before symptom onset and suggests that reliance on isolation of symptomatic COVID-19 cases as a focal point of control efforts is insufficient to address the challenges posed by SARS-CoV-2 transmission dynamics.